AI Software that Converts Brain Waves to Speech Invented

The development of a sophisticated AI system that
could decipher brain waves and convert them into intelligible speech marks a
remarkable breakthrough in the technology landscape. The system presents
promising prospects for the creation of brain-controlled communication devices.

While the idea of comprehending brain waves and
turning them into sensible speech has always remained prominent in the
scientific industry, the technology required to turn the idea into reality did
not exist until the recent past. With advanced machine learning algorithms, a
group of American neuroscientists has succeeded in developing a system that
could effectively turn brain waves into speech.

During the development of the system, data from five
patients who were undergoing neurosurgery for epilepsy was collected. A variety
of electrodes were implanted into the patients’ brains for measuring the
electrocorticography activity as they listened to continuous short stories
which were being narrated by four different people. Scientists only managed to
collect data worth 30 minutes owing to the invasive nature of gathering data
during neurosurgery.

The data collected from the patients was used to
train a vocoder. Scientists tested the efficiency of the algorithm by testing
it to decode voices of people counting from one to nine, data for which had not
been included while training the vocoder. As the patients recited digits, their
brain waves were recorded and analyzed by deep neural networks. The output from
the networks was cleaned and then produced by the vocoder.

The test revealed that the system was able to
convert brain waves into intelligible speech with an accuracy of almost 75%.
The results were groundbreaking as the amount of data used to train the neural
networks was minimal. Researchers believe the results suggest revolutionary
implications. However, scientists admitted that refining the system will take
almost a decade as data collection for training the algorithm requires
implantation of electrodes into the brain.

The team revealed that they will continue
refactoring the algorithm to test whether or not it can be used to produce more
complex sentences and words from the dataset available currently. The
integration of the technology with speech generating devices could be
groundbreaking and provide a voice to someone who has lost speech due to injury
or accident. In addition to this, the technology can help patients with speech
impairments as well. With time, the technology can aid in the proliferation of speech
generating devices sales opening new and lucrative
opportunities for the manufacturers.